研究队伍

姓  名:
宋春桥
性  别:
职  务:
研究室副主任
职  称:
研究员
学  历:
博士研究生
通讯地址:
江苏省南京市北京东路73号
电  话:
025-86882293
邮政编码:
210008
传  真:
 
电子邮件:
cqsong@niglas.ac.cn

简历:

工作简历

2017.12~今:   中国科学院南京地理与湖泊研究所,研究员

2014.10~2017.11  美国加州大学洛杉矶分校(UCLA),博士后

学习简历

2011.08~2014.07 香港中文大学,地理与资源管理系,博士

2013.04~2013.09 英国剑桥大学,地理系,博士交换生

2008.09~2011.06 中国科学院地理科学与资源研究所,地理信息系统,硕士

2004.09~2008.06 武汉大学,资源与环境科学学院,学士



研究领域:

水文水资源遥感与全球变化,青藏高原环境与气候变化影响

社会任职:

获奖及荣誉:

2017年,入选国家人才计划青年类;

2018年,入选江苏省人才项目;

2018年,入选江苏省“333人才工程”学术技术带头人;

2020年,获教育部科学研究优秀成果奖自然科学二等奖 (3rd);

2021年,国家人才计划青年项目(结题优秀);

2023年,获长江科学技术奖二等奖 (2nd)


代表论著:

主要论文(一作/通讯):

[1] Fan,C.,Song,C. *,Wang,J.,Sheng,Y.,Lin,Y.,Yuan,C.,Sikder,S.,Cretaux,J.,Liu,K.,Chen,T.,Zeng,F.,Ke,L. (2024). Emerging global reservoirs in the new millennium: abundance,hotspots,and total water storage. Science Bulletin. (TOP)

[2] Liu,K.,Song,C. *,Zhao,S.,Wang,J.,Chen,T.,Zhan,P.,Fan,C.,Zhu,J. (2024). Mapping inundated bathymetry for estimating lake water storage changes from SRTM DEM: a global investigation and implications for the Surface Water and Ocean Topography mission. Remote Sensing of Environment,301,113960. (TOP)

[3] Li,L.,Ning,Y.,Cao,Z.,Xue,K.,Song,C.*. (2024). Fine-scale monitoring of lake ice phenology by synthesizing remote sensed and climatologic features based on high-resolution satellite constellation and modeling. Science of the Total Environment: 169002. (TOP)

[4] Tong,J.,Lin,Y.,Fan,C.,Liu,K.,Chen,T.,Zeng,F.,Zhan,P.,Ke. L.,Gao,Y. *,Song,C.*. (2024). Fine-scale monitoring of lake ice phenology by synthesizing remote sensed and climatologic features based on high-resolution satellite constellation and modeling. Science of the Total Environment: 169002. (TOP)

[5] Feng,Y.,Song,C.* (2024). Assessing the impacts of ice penetration on monitoring water levels of high-latitude and -altitude lakes from CryoSat-2 altimetry. Journal of Hydrology. (TOP)

[6] Liu,K.,Zhang,D.,Chen,T.,Cui,P.,Fan,C.,Song,C. *. (2024) Monitoring Surface Water Change in Northeast China in 1999–2020: Evidence from Satellite Observation and Refined Classification. Chinese Geographical Sciences,34(1):106-117.

[7] Yuan,C.,Liu,C.,Fan,C.,Liu,K.,Chen,T.,Zeng,F.,Zhan,P.,Song,C. *. (2024) Estimation of water storage capacity of Chinese reservoirs by statistical and machine learning models. Journal of Hydrology,630,130674. (TOP)

[8] Yuan,C. #,Zhan,P.#,Fan,C.,Chen,T.,Zeng,F.,Liu,K.,Song,C. *. (2024) National estimation of water storage regulation capacity of reservoirs in China. Journal of Hydrology. (TOP)

[9] Ke,L.,Ding,X.,Ning,Y.,Liao,Y.,Song,C. *. (2024) Annual trajectory of global glacial lake variations and the interactions with glacier mass balance during 2013-2022. Catena. (TOP)

[10] Wu,Q.,Ke,L.,… & Song,C.*. (2023). Satellites reveal hotspots of global river extent change. Nature Communications,14(1),1587. (TOP)

[11] Zhan,P.,Song,C. *,Liu,K.,Chen,T.,Ke,L.,Luo,S.,& Fan,C. (2023). Can we estimate the lake mean depth and volume from the deepest record and auxiliary geospatial parameters?. Journal of Hydrology,617,128958. (TOP)

[12] Feng,Y.,Yang,L.,Zhan,P.,Luo,S.,Chen,T.,Liu,K.,& Song,C.*. (2023). Synthesis of the ICESat/ICESat-2 and CryoSat-2 observations to reconstruct time series of lake level. International Journal of Digital Earth,16(1),183-209. (TOP)

[13] Chen,T.,Song,C. *,Zhan,P.,& Fan,C. (2023). Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 Observations. Remote Sensing,15(3),780. (TOP)

[14] Song,L.,Song,C.*,Luo,S.,Chen,T.,Liu,K.,Zhang,Y.,& Ke,L. (2023). Integrating ICESat-2 altimetry and machine learning to estimate the seasonal water level and storage variations of national-scale lakes in China. Remote Sensing of Environment,294,113657. (TOP)

[15] Liang,X.,Song,C.,Liu,K.,Chen,T.,& Fan,C. (2023). Reconstructing Centennial-Scale Water Level of Large Pan-Arctic Lakes Using Machine Learning Methods. Journal of Earth Science,34(4),1218-1230.

[16] Zeng,F.,Song,C.,Cao,Z.,Xue,K.,Lu,S.,Chen,T.,& Liu,K. (2023). Monitoring inland water via Sentinel satellite constellation: A review and perspective. ISPRS Journal of Photogrammetry and Remote Sensing,204,340-361. (TOP)

[17] Cui,P.,Chen,T.,Li,Y.,Liu,K.,Zhang,D.,Song,C. (2023). Comparison and Assessment of Different Land Cover Datasets on the Cropland in Northeast China. Remote Sensing. 2023,15,5134. (TOP)

[18]  Luo,S.,Song,C. (2023). Uncertainties on the combined use of ICESat and ICESat-2 observations to monitor lake levels. Frontiers in Water,5,1279444.

[19] Song,C.*,Fan,C. *,Zhu,J. *,Wang,J.,Sheng,Y.,Liu,K.,...& Ke,L. (2022). A comprehensive geospatial database of nearly 100 000 reservoirs in China. Earth System Science Data,14(9),4017-4034. (TOP)

[20] Song,C. *,Jiang,X. *,Fan,C.,& Li,L. (2022). High-resolution circa-2020 map of urban lakes in China. Scientific Data,9(1),1-14.

[21] Song,C. *,Luo,S.,Liu,K. *,Chen,T.,Zhang,P.,& Fan,C. (2022). Widespread declines in water salinity of the endorheic Tibetan Plateau lakes. Environmental Research Communications,4(9),091002.

[22] Luo,S.,Song,C. *,Ke,L.,Zhan,P.,Fan,C.,Liu,K.,...& Zhu,J. (2022). Satellite laser altimetry reveals a net water mass gain in global lakes with spatial heterogeneity in the early 21st century. Geophysical Research Letters,49(3),e2021GL096676. (TOP)

[23] Ke,L.,Song,C. *,Wang,J.,Sheng,Y.,Ding,X.,Yong,B.,...& Luo,S. (2022). Constraining the contribution of glacier mass balance to the Tibetan lake growth in the early 21st century. Remote Sensing of Environment,268,112779. (TOP)

[24] Zhan,P.,Song,C. *,Luo,S.,Ke,L.,Liu,K.,& Chen,T. (2022). Investigating different timescales of terrestrial water storage changes in the northeastern Tibetan Plateau. Journal of Hydrology,608,127608. (TOP)

[25] Jiang,X.,Fan,C.,Liu,K.,Chen,T.,Cao,Z.,& Song,C*. (2022). Centenary covariations of water salinity and storage of the largest lake of Northwest China reconstructed by machine learning. Journal of Hydrology,612,128095. (TOP)

[26] Liu,K.,& Song,C*. (2022). Modeling lake bathymetry and water storage from DEM data constrained by limited underwater surveys. Journal of Hydrology,604,127260. (TOP)

[27] Chen,T.,Song,C. *,Luo,S.,Ke,L.,Liu,K.,& Zhu,J. (2022). Monitoring global reservoirs using ICESat-2: Assessment on spatial coverage and application potential. Journal of Hydrology,604,127257. (TOP)

[28] Chen,T.,Song,C. *,Zhan,P.,Yao,J.,Li,Y.,& Zhu,J. (2022). Remote sensing estimation of the flood storage capacity of basin-scale lakes and reservoirs at high spatial and temporal resolutions. Science of the Total Environment,807,150772. (TOP)

[29] Cheng,J.,Song,C. *,Liu,K.,Fan,C.,Ke,L.,Chen,T.,...& Yao,J. (2022). Satellite and UAV-based remote sensing for assessing the flooding risk from Tibetan lake expansion and optimizing the village relocation site. Science of the Total Environment,802,149928. (TOP)

[30] Chen,T.,Song,C. *,Fan,C.,Cheng,J.,Duan,X.,Wang,L.,...& Che,Y. (2022). A comprehensive data set of physical and human-dimensional attributes for China’s lake basins. Scientific Data,9(1),1-15.

[31] Fan,C.,Liu,K. *,Luo,S.,Chen,T.,Cheng,J.,Zhan,P.,& Song,C*. (2022). Detection of surface water temperature variations of Mongolian lakes benefiting from the spatially and temporally gap-filled MODIS data. International Journal of Applied Earth Observation and Geoinformation,114,103073. (TOP)

[32] Liu,K.,Na,J.,Fan,C.,Huang,Y.,Ding,H.,Wang,Z.,...& Song,C*. (2022). Large-Scale Detection of the Tableland Areas and Erosion-Vulnerable Hotspots on the Chinese Loess Plateau. Remote Sensing,14(8),1946. (TOP)

[33] Ke,L.,Zhang,J.,Fan,C.,Zhou,J.,& Song,C*. (2022). Large-Scale Monitoring of Glacier Surges by Integrating High-Temporal-and-Spatial-Resolution Satellite Observations: A Case Study in the Karakoram. Remote Sensing,14(18),4668. (TOP)

[34] Chen,T.,Song,C. *,Zhan,P.,& Ma,J. (2022). How Many Pan-Arctic Lakes Are Observed by ICESat-2 in Space and Time?. Remote Sensing,14(23),5971. (TOP)

[35] Ke,L.,Xu,J.,Fan,C.,Liu,K.,Chen,T.,Wang,S.,...& Song,C*. (2022). Remote sensing reconstruction of long-term water level and storage variations of a poorly-gauged river in the Tibetan Plateau. Journal of Hydrology: Regional Studies,40,101020. 

[36] Song,L.,Song,C. *,Zhan,P.,Chen,T.,Liu,K.,& Jing,H. (2022). Seasonal amplitude of water storage variations of the Yangtze-Huai Plain lake group: Implication for floodwater storage capacity. Frontiers in Environmental Science,33.

[37] Chen,T.,Song,C. *,Fan,C.,Gao,X.,Liu,K.,Li,Z.,...& Zhan,P. (2022). Remote sensing modeling of environmental influences on lake fish resources by machine learning: A practice in the largest freshwater lake of China. Frontiers in Environmental Science,1233.

[38] Liu,K.,Song,C. *,Zhan,P.,Luo,S.,& Fan,C. (2022). A Low-Cost Approach for Lake Volume Estimation on the Tibetan Plateau: Coupling the Lake Hypsometric Curve and Bottom Elevation. Frontiers in Earth Science,10,925944.

[39] Fan,C.,Song,C. *,Liu,K.,Ke,L.,Xue,B.,Chen,T.,...& Cheng,J. (2021). Century‐Scale Reconstruction of Water Storage Changes of the Largest Lake in the Inner Mongolia Plateau Using a Machine Learning Approach. Water Resources Research,57(2),e2020WR028831. (TOP)

[40] Fan,C.,Song,C. *,Li,W.,Liu,K.,Cheng,J.,Fu,C.,...& Wang,J. (2021). What drives the rapid water-level recovery of the largest lake (Qinghai Lake) of China over the past half century?. Journal of Hydrology,593,125921. (TOP)

[41] Chen,T.,Song,C. *,Ke,L.,Wang,J.,Liu,K.,& Wu,Q. (2021). Estimating seasonal water budgets in global lakes by using multi-source remote sensing measurements. Journal of Hydrology,593,125781. (TOP)

[42] Liu,K.#,Ke,L.#,Wang,J.,Jiang,L.,Richards,K. S.,Sheng,Y.,...& Song,C*. (2021). Ongoing drainage reorganization driven by rapid lake growths on the Tibetan Plateau. Geophysical Research Letters,48(24),e2021GL095795. (TOP)

[43] Luo,S.,Song,C. *,Zhan,P.,Liu,K.,Chen,T.,Li,W.,& Ke,L. (2021). Refined estimation of lake water level and storage changes on the Tibetan Plateau from ICESat/ICESat-2. Catena,200,105177. (TOP)

[44] Song,L.,Song,C. *,Luo,S.,Chen,T.,Liu,K.,Li,Y.,...& Xu,J. (2021). Refining and densifying the water inundation area and storage estimates of Poyang Lake by integrating Sentinel-1/2 and bathymetry data. International Journal of Applied Earth Observation and Geoinformation,105,102601. (TOP)

[45] Cheng,J.,Song,C. *,Liu,K.,Ke,L.,Chen,T.,& Fan,C. (2021). Regional assessment of the potential risks of rapid lake expansion impacting on the Tibetan human living environment. Environmental Earth Sciences,80(4),1-14.

[46] Zhan,P.,Song,C. *,Luo,S.,Liu,K.,Ke,L.,& Chen,T. (2021). Lake level reconstructed from DEM-based virtual station: Comparison of multisource DEMs with laser altimetry and UAV-LiDAR measurements. IEEE Geoscience and Remote Sensing Letters,19,1-5.

[47] Zhu,J.,Song,C. *,Ke,L.,Liu,K.,& Chen,T. (2021). Remote Sensing Investigation of the Offset Effect between Reservoir Impoundment and Glacier Meltwater Supply in Tibetan Highland Catchment. Water,13(9),1307.

[48] Ma,J.,Song,C. *,& Wang,Y. (2021). Spatially and temporally resolved monitoring of glacial lake changes in Alps during the recent two decades. Frontiers in Earth Science,760.

[49] Song,C. *,Sheng,Y.,Zhan,S.,Wang,J.,Ke,L.,& Liu,K. (2020). Impact of amplified evaporation due to lake expansion on the water budget across the inner Tibetan Plateau. International Journal of Climatology,40(4),2091-2105.

[50] Zhu,J.,Song,C. *,Wang,J.,& Ke,L. (2020). China’s inland water dynamics: The significance of water body types. Proceedings of the National Academy of Sciences,117(25),13876-13878. (TOP)

[51] Ke,L.,Song,C. *,Yong,B.,Lei,Y.,& Ding,X. (2020). Which heterogeneous glacier melting patterns can be robustly observed from space?A multi-scale assessment in southeastern Tibetan Plateau. Remote Sensing of Environment,242,111777. (TOP)

[52] Deng,X.,Song,C. *,Liu,K.,Ke,L.,Zhang,W.,Ma,R.,...& Wu,Q. (2020). Remote sensing estimation of catchment-scale reservoir water impoundment in the upper Yellow River and implications for river discharge alteration. Journal of Hydrology,585,124791. (TOP)

[53] Liu,K.,Song,C. *,Wang,J.,Ke,L.,Zhu,Y.,Zhu,J.,...& Luo,Z. (2020). Remote sensing‐based modeling of the bathymetry and water storage for channel‐type reservoirs worldwide. Water Resources Research,56(11),e2020WR027147. (TOP)

[54] Liu,K.,Song,C. *,Ke,L.,Jiang,L.,& Ma,R. (2020). Automatic watershed delineation in the Tibetan endorheic basin: A lake-oriented approach based on digital elevation models. Geomorphology,358,107127. 

[55] Wu,Q.,Song,C. *,Liu,K.,& Ke,L. (2020). Integration of TanDEM-X and SRTM DEMs and spectral imagery to improve the large-scale detection of opencast mining areas. Remote Sensing,12(9),1451. (TOP)

[56] Zhan,P.,Song,C. *,Wang,J.,Li,W.,Ke,L.,Liu,K.,& Chen,T. (2020). Recent abnormal hydrologic behavior of Tibetan lakes observed by multi-mission altimeters. Remote Sensing,12(18),2986. (TOP)

[57] Zhan,S.,Song,C. *,Wang,J.,Sheng,Y.,& Quan,J. (2019). A global assessment of terrestrial evapotranspiration increase due to surface water area change. Earth's Future,7(3),266-282. (TOP)

[58] Liu,K.,Song,C. *,Ke,L.,Jiang,L.,Pan,Y.,& Ma,R. (2019). Global open-access DEM performances in Earth's most rugged region High Mountain Asia: A multi-level assessment. Geomorphology,338,16-26.

[59] Luo,S.,Song,C. *,Liu,K.,Ke,L.,& Ma,R. (2019). An effective low-cost remote sensing approach to reconstruct the long-term and dense time series of area and storage variations for large lakes. Sensors,19(19),4247.

[60] Song,C. *,Ke,L.,Pan,H.,Zhan,S.,Liu,K.,& Ma,R. (2018). Long-term surface water changes and driving cause in Xiong’an,China: From dense Landsat time series images and synthetic analysis. Science Bulletin,63(11),708-716. (TOP)

[61] Wang,J. #*,Song,C.#,Reager,J. T.,Yao,F.,Famiglietti,J. S.,Sheng,Y.,...& Wada,Y. (2018). Recent global decline in endorheic basin water storages. Nature Geoscience,11(12),926-932. (TOP)

[62] Zhang,W.,Pan,H.,Song,C. *,Ke,L.,Wang,J.,Ma,R.,...& Wu,Q. (2018). Identifying emerging reservoirs along regulated rivers using multi-source remote sensing observations. Remote Sensing,11(1),25. (TOP)

[63] Wu,Q.,Liu,K.,Song,C. *,Wang,J.,Ke,L.,Ma,R.,...& Deng,X. (2018). Remote sensing detection of vegetation and landform damages by coal mining on the Tibetan Plateau. Sustainability,10(11),3851.

[64] Song,C. *,Sheng,Y.,Wang,J.,Ke,L.,Madson,A.,& Nie,Y. (2017). Heterogeneous glacial lake changes and links of lake expansions to the rapid thinning of adjacent glacier termini in the Himalayas. Geomorphology,280,30-38. 

[65] Sheng,Y. *,Song,C.,Wang,J.,Lyons,E. A.,Knox,B. R.,Cox,J. S.,& Gao,F. (2016). Representative lake water extent mapping at continental scales using multi-temporal Landsat-8 imagery. Remote Sensing of Environment,185,129-141. (TOP)

[66] Song,C. *,Sheng,Y. *,Ke,L.,Nie,Y.,& Wang,J. (2016). Glacial lake evolution in the southeastern Tibetan Plateau and the cause of rapid expansion of proglacial lakes linked to glacial-hydrogeomorphic processes. Journal of Hydrology,540,504-514. (TOP)

[67] Song,C.,& Sheng,Y*. (2016). Contrasting evolution patterns between glacier-fed and non-glacier-fed lakes in the Tanggula Mountains and climate cause analysis. Climatic Change,135(3),493-507.

[68] Song,C. *,Huang,B. *,Ke,L.,& Ye,Q. (2016). Precipitation variability in High Mountain Asia from multiple datasets and implication for water balance analysis in large lake basins. Global and Planetary Change,145,20-29. (TOP)

[69] Song,C. *,Ke,L.,Richards,K. S.,& Cui,Y. (2016). Homogenization of surface temperature data in High Mountain Asia through comparison of reanalysis data and station observations. International Journal of Climatology,36(3),1088-1101.

[70] Song,C.,Ye,Q. *,& Cheng,X. (2015). Shifts in water-level variation of Namco in the central Tibetan Plateau from ICESat and CryoSat-2 altimetry and station observations. Science Bulletin,60(14),1287-1297. (TOP)

[71] Song,C. *,Ke,L. *,Huang,B.,& Richards,K. S. (2015). Can mountain glacier melting explains the GRACE-observed mass loss in the southeast Tibetan Plateau: From a climate perspective?. Global and Planetary Change,124,1-9. (TOP)

[72] Song,C. *,Huang,B. *,& Ke,L. (2015). Heterogeneous change patterns of water level for inland lakes in High Mountain Asia derived from multi‐mission satellite altimetry. Hydrological Processes,29(12),2769-2781.

[73] Song,C. *,Ye,Q. *,Sheng,Y.,& Gong,T. (2015). Combined ICESat and CryoSat-2 altimetry for accessing water level dynamics of Tibetan lakes over 2003–2014. Water,7(9),4685-4700.

[74] Song,C.,Huang,B. *,Ke,L.,& Richards,K. S. (2014). Remote sensing of alpine lake water environment changes on the Tibetan Plateau and surroundings: A review. ISPRS Journal of Photogrammetry and Remote Sensing,92,26-37. (TOP)

[75] Ke,L.,& Song,C*. (2014). Remotely sensed surface temperature variation of an inland saline lake over the central Qinghai–Tibet Plateau. ISPRS Journal of Photogrammetry and Remote Sensing,98,157-167. (TOP)

[76] Song,C.,Huang,B. *,Richards,K.,Ke,L.,& Hien Phan,V. (2014). Accelerated lake expansion on the Tibetan Plateau in the 2000s: Induced by glacial melting or other processes?. Water Resources Research,50(4),3170-3186. (TOP)

[77] Song,C. *,Huang,B. *,Ke,L.,& Richards,K. S. (2014). Seasonal and abrupt changes in the water level of closed lakes on the Tibetan Plateau and implications for climate impacts. Journal of Hydrology,514,131-144. (TOP)

[78] Song,C.,Huang,B. *,& Ke,L. (2014). Inter‐annual changes of alpine inland lake water storage on the Tibetan Plateau: Detection and analysis by integrating satellite altimetry and optical imagery. Hydrological Processes,28(4),2411-2418.

[79] Song,C.,& Ke,L*. (2014). Recent dramatic variations of China’s two largest freshwater lakes: Natural process or influenced by the Three Gorges Dam?. Environmental Science & Technology,48(3),2086-2087. (TOP)

[80] Song,C.,Huang,B. *,& Ke,L. (2013). Modeling and analysis of lake water storage changes on the Tibetan Plateau using multi-mission satellite data. Remote Sensing of Environment,135,25-35. (TOP)

[81] 刘沭岍,刘凯,曾繁轩,& 宋春桥*. (2024). 河流水文遥感及其在青藏高原应用研究进展. 遥感学报. 

[82] 童洁,高永年,詹鹏飞,& 宋春桥*. (2023). 湖冰遥感研究进展. 遥感学报,1-20. 

[83] 宋利娟,景海涛,徐嘉慧,陈探,张大鹏,& 宋春桥*. (2023). 联合哨兵卫星系列雷达与光学影像的洞庭湖水域面积变化高时空分辨率监测. 遥感学报,27(11),2516-2529. 

[84] 李林森,王涵,刘凯,宁一航,陈思,& 宋春桥*. (2023). 我国城市湖泊空间分布格局特征分析及影响因素探讨. 湖泊科学,1-16.

[85] 梁新歌,王涵,赵爽,& 宋春桥*. (2023). 21世纪以来泛北极湖泊水位变化时空特征及原因探讨. 湖泊科学,35(6),2111-2122.

[86] 徐嘉慧,王世东,宋利娟,张大鹏,& 宋春桥*. (2022). 雅鲁藏布江干流河宽时空变化遥感监测及水文气象响应. 地理学报,77(11),2862-2877.

[87] 张闻松,& 宋春桥*. (2022). 中国湖泊分布与变化:全国尺度遥感监测研究进展与新编目. 遥感学报. 26(01),92-103.

[88] 程俭,刘昌华,刘凯,武建双,范晨雨,薛滨,...& 宋春桥*. (2021). 2004 年以来青海湖快速扩张对人居设施与草地的潜在影响. 湖泊科学,33(3),922-934.

[89] 宋春桥*,詹鹏飞,& 马荣华. (2020). 湖泊水情遥感研究进展. 湖泊科学,32(5),1406-1420.

[90] 罗竹,刘凯,张春亢,邓心远,马荣华,& 宋春桥*. (2020). DEM 在湖泊水文变化研究中的应用进展. 地球信息科学学报,22(7),1510-1521.

[91] 宋春桥,叶庆华*,& 程晓. (2015). 基于 ICESat/CryoSat-2 卫星测高及站点观测的纳木错湖水位趋势变化监测. 科学通报,(21),2048-2048.

[92] 宋春桥,游松财*,刘高焕,柯灵红,& 钟新科. (2012). 那曲地区草地植被时空格局与变化及其人文因素影响研究. 草业学报,21(3),1-10.

[93] 傅新,宋春桥*,& 钟新科. (2012). 藏北高原土壤湿度时空变化分析. 水科学进展,23(4),464-474.

[94] 宋春桥*,游松财,柯灵红,刘高焕,& 钟新科. (2012). 藏北高原土壤湿度MODIS遥感监测研究. 土壤通报,43(02),294-300.

[95] 宋春桥,游松财*,柯灵红,刘高焕,& 钟新科. (2012). 藏北高原典型植被样区物候变化及其对气候变化的响应. 生态学报,32(4),1045-1055.

[96] 宋春桥,游松财*,柯灵红,刘高焕,& 钟新科. (2011). 藏北高原地表覆盖时空动态及其对气候变化的响应. 应用生态学报,22(8),2091-2097.

[97] 宋春桥*,游松财,柯灵红,& 刘高焕. (2011). 藏北地区三种时序NDVI重建方法与应用分析. 地球信息科学学报,13(01),133-143. (EI)

[98] 宋春桥*,柯灵红,游松财,刘高焕,& 钟新科. (2011). 基于TIMESAT的3种时序NDVI拟合方法比较研究—以藏北草地为例. 遥感技术与应用,26(2),147-155.

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主编论著:

《Remote Sensing of Lake Hydrology in the Tibetan Plateau: Pattern,Drivers and Impacts》,2024,Science Press出版社,主编.

《Comprehensive Geographic Information Systems》,2017,Elsevier出版集团,共同主编.


承担科研项目情况:

1. 2017.12~2021.12,湖泊流域水文遥感与全球变化,国家人才计划青年项目,项目负责人;

2. 2020.01~2023.12,典型湖泊群水储量估算模型研究——以青藏高原湖区为例,国家自然科学基金委面上项目,项目负责人;

3. 2024.01~2027.12,基于遥感虚拟星座的青藏高原内流河水文变化监测,国家自然科学基金委面上项目,项目负责人;

4. 2018.12~2022.12,渔业生境退化和生物多样性演变的评估理论与方法,国家重点研发计划项目,课题负责人;

5. 2022.11~2026.10,地球表层系统关键参数自动生成与挖掘分析,国家重点研发计划项目,课题负责人;

6. 2019.01~2023.12,美丽中国-“原真地理特征与生态文明模式时空规律及形成机制”,中国科学院A类战略性先导科技专项子课题,子课题负责人;

7. 2018.12~2022.12,村镇建设资源环境承载力测算系统开发,国家重点研发计划项目,核心骨干/项目中心组;

8. 2019.11~2024.10,亚洲水塔动态变化与影响,国家第二次青藏高原综合科学考察研究,核心骨干.